A new metrological characterization strategy for 3D multi-camera systems

AbstractThe objective of this study is to establish a new methodology for the metrological characterization of interactive multi-camera systems. In the case of 3D system highly adapted to specific needs the accuracy evaluation cannot be performed using standard state-of-the-art techniques. To this end, the metrological characterization techniques used in the literature were investigated in order to define a new methodology that can be adjusted to each device by making the appropriate modifications. The proposed strategy is adopted for the metrological characterization of a new interactive multi-camera system for the acquisition of the arm

Design of an automatic optical system to measure anthropometric hand parameters

AbstractPersonalized medicine is an effective tool to improve the quality of rehabilitation and treatment for patients with disabilities. This study deals with the development of a low-cost hand scanner for the acquisition of anthropometric measures. The data acquired by the scanner is used, thanks to the developed procedure, to tailor the dimensions of a hand exoskeleton. The exoskeleton is used for assistive and rehabilitation purposes

A computer-aided strategy for preoperative simulation of autologous ear reconstruction procedure

AbstractAutologous ear reconstruction is the preferred treatment in case of partial or total absence of the external ear. The surgery can be very challenging to perform and the aesthetic result highly dependent on the surgeon's "artistic skills". In this context a preoperative planning and simulation phase based on the patient's specific anatomy may result crucial for the surgical outcome. In this work, starting from a case study, the elements necessary for an effective simulation are identified and a strategy for their interactive design and customization is devised with a perspective of a semi-automatization of the procedure

How to best predict short bowel syndrome outcome with machine learning approaches

Abstract In recent years, there has been an extensive use of machine learning techniques in the medical field for diagnostic or therapeutic prediction purposes. In the field of short bowel syndrome, numerous statistical studies have been proposed, but to date no machine learning techniques have been exploited to predict the outcomes of the surgery commonly performed in paediatric patients suffering from this pathology. One reason for this lack can be identified in the fact that this is a rare condition and therefore it is difficult to have a large dataset. This paper investigates the possibility of processing demographic data of paediatric short bowel syndrome patients by spot-checking machine learning algorithms on a dataset of 86 patients. The experimental setup was developed to ensure the best performance of each algorithm and to take into account the moderate unbalance of the output classes. The Decision Tree algorithms proved to be the best solution in terms of accuracy, precision, recall and F1-score (obtaining values of 0.85 for each metric considered), capable of better understanding the data model

A Fast and Reliable Optical 3D Scanning System for Human Arm

AbstractThe article discusses the design of an acquisition system for the 3D surface of human arms. The system is composed by a 3D optical scanner implementing stereoscopic depth sensors and by an acquisition software responsible for the processing of the raw data. The 3D data acquired by the scanner is used as starting point for the manufacturing of custom-made 3D printed casts. Specifically, the article discusses the choices made in the development of an improved version of an existing system presented in [1] and presents the results achieved by the devised system

A Machine Vision-Based Algorithm for Color Classification of Recycled Wool Fabrics

The development of eco-sustainable systems for the textile industry is a trump card for attracting expanding markets aware of the ecological challenges that society expects in the future. For companies willing to use regenerated wool as a raw material for creating plain, colored yarns and/or fabrics, building up a number of procedures and tools for classifying the conferred recycled materials based on their color is crucial. Despite the incredible boost in automated or semi-automated methods for color classification, this task is still carried out manually by expert operators, mainly due to the lack of systems taking into account human-related classification. Accordingly, the main aim of the present work was to devise a simple, yet effective, machine vision-based system combined with a probabilistic neural network for carrying out reliable color classification of plain, colored, regenerated wool fabrics. The devised classification system relies on the definition of a set of color classes against which to classify the recycled wool fabrics and an appositely devised acquisition system. Image-processing algorithms were used to extract helpful information about the image color after a set of images has been acquired. These data were then used to train the neural network-based algorithms, which categorized the fabric samples based on their color. When tested against a dataset of fabrics, the created system enabled automatic classification with a reliability index of approximately 83%, thus demonstrating its effectiveness in comparison to other color classification approaches devised for textile and industrial fields

Comparison of Mesh Simplification tools in a 3D Watermarking framework

Given a to-be-watermarked 3D model, a transformed domain analy-sis is needed to guarantee a robust embedding without compromising the visual quality of the result. A multiresolution remeshing of the model allows to repre-sent the 3D surface in a transformed domain suitable for embedding a robust and imperceptible watermark signal. Simplification of polygonal meshes is the basic step for a multiresolution remeshing of a 3D model; this step is needed to obtain the model approximation (coarse version) from which a refinement framework (i.e. 3D wavelet analysis, spectral analysis, \u2026) able to represent the model at multiple resolution levels, can be performed. The simplification algo-rithm should satisfy some requirements to be used in a watermarking system: the repeatability of the simplification, and the robustness of it to noise or, more generally, to slight modifications of the full resolution mesh. The performance of a number of software packages for mesh simplification, including both commercial and academic offerings, are compared in this survey. We defined a benchmark for testing the different software in the watermarking scenario and reported a comprehensive analysis of the software performances based on the geometric distortions measurement of the simplified versions